Evaluating Risks and Establishing Food Safety Objectives and Performance Objectives
2.3 Importance of Epidemiologic Data
Accurate knowledge of disease incidence and severity is critical for competent national authorities for use in shaping risk-based public policy, including setting ALOP or TLR and selecting appropriate manage-ment actions to reduce the overall public health impact, including FSO and/or PO or other options.
Levels of risk to consumers in a country are generally articulated in relation to the mortality or morbidity of a disease, expressed as a number of cases (morbidity) or deaths (mortality) for a certain size of population per period of time. For many reasons the “true” incidence of foodborne disease is not known. At best, reasonable estimates can be developed for particular diseases because the impact on the consumer is profound and the characteristics of the diseases are sufficiently evident.
At the basis of any articulation of risk, e.g., current risk, tolerable risk or future goals to mitigate risks, lies the collection, synthesis and analysis of data from a number of epidemiologic data sources that together signal the emergence or existence of food safety problems, characterize them and allow assessment of the effectiveness of control measures at the levels of the food supply and the human population (Table 2.2). The following datasets are considered to be within the scope of epidemiologic data (ICMSF 2006a):
• data derived from vital records, registries, and surveillance of clinical diseases in humans, plants, and animals
• data from epidemiologic investigations of outbreaks and other special public health studies
• data from laboratory-based surveillance of pathogens isolated from humans, plants, animals, and food processing environments
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• monitoring data derived from regulatory and non-regulatory sampling of foods, including micro-bial food testing
• environmental health data on practices and procedures of food workers
• data from behavioral surveillance of consumer habits and practices.
Information from various sources is very important to compile, analyze and understand in terms of the burden of illness on a population and to assess the effect of policies instituted to thwart foodborne dis-ease. Several approaches are currently used to monitor and report the incidence of foodborne diseases:
• passive notification systems
• active surveillance systems
• case control studies
• outbreak investigations
• sentinel studies
None of these systems yield all the data necessary for a quantitative risk assessment and some (e.g., passive notification systems) often fail to identify food as a source. Passive notification systems follow trends in disease and can be useful for measuring the impact of changes in technology, preventive measures and regulatory policies. For example, Fig. 2.1 shows the reported incidence of salmonellosis and shigellosis in the U.S.A. from 1980 through to 2013 (CDC 2015a). The data were developed through reports from local sources in each state and then submitted from the state to the Centers for Disease Control and Prevention. In addition, physicians have been required to report particular “notifi-able” diseases. This mandatory requirement can strengthen the accuracy of the data but many cases remain unreported. Similarly, reports from laboratories can identify trends for instance in non- typhoidal Salmonella cases and identify for public health officials changing risks to the population (Fig. 2.2).
Another approach to collecting data on the incidence of disease is through active surveillance sys-tems such as EnterNet or FoodNet (MMWR 2000, 2013). EnterNet has been established to determine
Table 2.2 Surveillance data needs within the food chain for adequate evaluation of prevention effectiveness (ICSMF 2006a, b)
Pre-harvest Country-level surveillance of food animal and plant diseases and the occurrence of pathogenic agents transmissible to humans through food should be able to rank commodities by frequency of contamination and determine subtype/fingerprint of hazards by animal or plant of origin, geographic origin, production practices and conditions, and season.
Harvest, processing, distribution
Country-level microbial surveillance and monitoring programs should be able to rank specific foods by frequency of contamination, and determine subtype/fingerprint of hazard by food, process, step in process, geographic origin, and season.
Retail food service, retail sale and home preparation
Country-level microbial surveillance and environmental sanitation and behavioral risk factor surveys should be able to: (1) rank specific foods at retail by frequency of contamination, (2) associate environmental antecedents (practices, processes, behaviors, and equipment) at retail with product contamination, (3) provide a subtype/fingerprint catalog of hazard by food, practice, process, behavior, geographic origin, and season, and (4) characterize consumer-induced risk factors for foodborne disease (e.g., host factors, food choices, and home food handling practices).
Public health surveillance
Country-level public health surveillance systems should be able to estimate frequency of adverse health events from hazards that are frequently foodborne and track the occurrence of infections that can be transmitted from infected persons to consumers through contamination of food. Routine epidemiologic studies of sporadic foodborne disease should be able to allocate the relative proportion of major hazards attributable to specific foods, at least within broad food categories.
Country-level outbreak investigations and surveillance should be able to identify food sources of epidemic disease and allocate the relative proportion of major hazards attributable to specific foods, processes, practices, behaviors, and host characteristics for epidemic disease. Enhanced attribution of foodborne illness to specific foods, processes, and behaviors is essential for accurate assessment of the public health effectiveness of management strategies.
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more accurately the incidence of salmonellosis and infections caused by E. coli O157 in Europe. Another goal of EnterNet is to establish a system to identify outbreaks in Europe from a common food source.
First established in the USA in 1996, and later duplicated and implemented in several regions around the world, the Foodborne Diseases Active Surveillance Network or, FoodNet, is an active, sentinel site pro-gram that collects weekly updates from clinicians in certain regions of the country for specific foodborne illnesses, including Campylobacter, Cryptosporidium, Cyclospora, Listeria, Salmonella, Shiga toxin-producing Escherichia coli (STEC) O157 and non-O157, Shigella, Vibrio and Yersinia. Isolates of selected pathogens are compared for commonality to identify outbreaks due to a common food source.
FoodNet estimates the number of foodborne illnesses in the USA, monitors trends in incidence of spe-cific foodborne illnesses over time, attributes illnesses to spespe-cific foods and settings, and disseminates
Fig. 2.1 Trend in the incidence per 100,000 population of salmonellosis and shigellosis cases in the United States from 1980 to 2013 (CDC 2015a)
Fig. 2.2 Laboratory reports of non-typhoidal human Salmonella cases in the UK, 1994–2013 (DEFRA 2015) 2 Evaluating Risks and Establishing Food Safety Objectives and Performance Objectives
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this information. Table 2.3 summarizes surveillance data collected by FoodNet between 1996 and 2014 in terms of rates of incidents for various illnesses tracked. For the relevant illnesses, the rates assessed are compared to the stated public health goals under the Healthy People 2010 and 2020 initia-tives (FDA/FSIS 2001, 2010), showing the USA’s ambition for continuous improvement of public health protection.
It is difficult to compare outcomes of epidemiological surveillance between different countries or regions in the world. Surveillance systems differ and most capture only a proportion of the cases occurring in their country/region. Moreover, cases of particular diseases remain undiagnosed (aka under-ascertainment) and/or diagnosed but not reported to public health authorities (aka underreport-ing). Under- ascertainment and underreporting levels vary by disease and country/regions as it involves a complex mix of healthcare-seeking behavior, access to health services, availability of diagnostic tests, reporting practices by doctors and others, and the operation of the surveillance system itself.
Even within a harmonized region such as the European Union, data provided by the 26 Member States on the 52 communicable diseases and health issues for which surveillance is mandatory show incon-sistencies for these and other reasons (ECDC 2014).
Data on foodborne disease is also collected through case control studies by interviewing patients to learn their food consumption history and to identify food sources. In parallel, a number of individu-als are selected to serve as controls. This methodology has been used to identify not only the foods that may be involved, but also risk factors that the patients may share and that may explain increased susceptibility to the disease. Case-control studies are useful for identifying pathogen-food combina-tions where it has been difficult to isolate the causative organism from the food source or the role of foods in diseases with long incubation times before onset of symptoms (e.g. listeriosis).
Table 2.3 Incidence per 100,000 population of culture-confirmed bacterial and laboratory-confirmed parasitic infections, and post-diarrheal hemolytic uremic syndrome (HUS), by year and pathogen, in the United States between 1996 and 2014 by the Foodborne Diseases Active Surveillance and reference incidences from the National Health Objective (NHO) for 2010 and 2020 (amended from CDC 2015b)
Pathogen/syndrome
Year NHO
2010§ NHO 2020¶
2000 2002 2006 2008 2010 2012 2014 2014
Campylobacter 15.36 13.38 12.73 12.65 13.53 14.22 13.45 13.45 12.3 8.5
Listeria* 0.33 0.25 0.28 0.26 0.27 0.26 0.24 0.24 0.24 0.2
Salmonella 14.08 16.24 14.76 16.10 17.55 16.38 15.45 15.45 6.8 11.4
Shigella 7.67 10.86 6.10 6.57 3.77 4.47 5.81 5.81 N/A† N/A
STEC§§ O157 2.03 1.69 1.30 1.12 0.95 1.11 0.92 0.92 1.0 0.6
STEC non- O157 0.19 0.16 0.53 0.53 0.96 1.16 1.43 1.43 N/A N/A
Vibrio 0.18 0.27 0.34 0.29 0.41 0.41 0.45 0.45 N/A 0.2
Yersinia 0.43 0.45 0.36 0.36 0.34 0.33 0.28 0.28 N/A 0.3
Cryptosporidium 1.57 1.32 1.94 2.27 2.75 2.63 2.44 2.44 N/A N/A
Cyclospora 0.06 0.10 0.09 0.04 0.06 0.03 0.05 0.05 N/A N/A
HUS** 2.04 2.05 2.21 1.71 1.88 1.47 – – N/A 0.9
Surveillance population
(millions)*** 30.64 37.86 45.32 46.33 47.15 47.89 48.24 48.24
§, ¶: National Health Objective target for incidence of indicated pathogen in Healthy People 2010 and 2020, respec-tively
*: Listeria cases defined as isolation of L. monocytogenes from a normally sterile site or, in the setting of miscarriage or stillbirth, isolation of L. monocytogenes from placental or fetal tissue
†: No National Health Objective exists for the indicated pathogen
§§: Shiga toxin-producing Escherichia coli
¶¶: Surveillance not conducted for this pathogen in this year
**Incidence of postdiarrheal HUS in children aged <5 years; denominator is surveillance population aged <5 years
***Preliminary U.S. Census Bureau population estimates for 2013 2.3 Importance of Epidemiologic Data
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The identity of the food source and conditions leading to foodborne illness may also be determined through epidemiologic investigations of outbreaks. Unfortunately, not all outbreaks are adequately investigated or described fully in the scientific literature, particularly those that do not provide new infor-mation. Consequently, that literature is often of limited use in relation to establishing the true frequency of their occurrence and thus the risk(s) associated with the disease agent. Case control studies can also be used to help identify the source(s) of sporadic cases of foodborne illness and the factors that contrib-ute to their frequency. Different sources may be more important in sporadic cases than in outbreaks. In the USA, outbreaks of Campylobacter jejuni infections in the spring and fall are typically caused by drinking raw unpasteurized milk or untreated water, whereas sporadic cases occurring in the summer appear related to touching or consuming uncooked poultry (Potter and Tauxe 1997; Tauxe 1992).
A sentinal study monitors selected health events in a group of persons representative of the whole population. Laboratory testing may be limited, e.g., to patients reporting diarrhea, or may include examination of all fecal samples for a range of pathogens. This approach, for instance, has been used to estimate the incidence of campylobacteriosis and salmonellosis in The Netherlands (Notermans and Hoogenboom-Verdegaal 1992) and England (Wheeler et al. 1999; FSA 2000).
However, much of the information collated regarding foodborne illnesses by different systems can-not be directly translated into policy since:
– not all cases are reported to health authorities, resulting in considerable uncertainty about the actual burden of illness
– often only a fraction of illnesses caused by food-related pathogens are actually foodborne because transmission can also be through the environment, direct contact with animals, or from person to person
– foodborne illnesses may vary both in incidence and severity, resulting in widely different clinical manifestations and potential likelihood of long-term sequelae.
Targeted studies in a number of countries have attempted to estimate the magnitude of underreport-ing. Mead et al. (1999) for instance estimated underreporting factors for different illnesses ranging from 2 for botulism and listeriosis, 20 for EHEC and shigellosis, and 38 for campylobacterioses and salmo-nellosis. In general, the estimates generated by such studies reflect a similar degree of magnitude in countries of similar economic development, demographics and healthcare infrastructure, but differences do exist. According to European studies similar to the one conducted in the USA, found the underreport-ing factors for campylobacteriosis were 7.6 (Wheeler et al. 1999) and 10.3 (Adak et al. 2002), while these studies reported underreporting factors of 3.2 and 3.9, respectively, for salmonellosis.